Senior AI Engineer

I hope you are doing well!

My name is Aditya Kumar from Stellent IT LLC. I am reaching out to you on an new job opportunity. If are you Comfortable with Below Position then please share me your updated resume.

Job Tite: Senior AI Engineer

Location: Remote

Duration: Nov 2, 2026 Feb 9, 2027

JOB DESCRIPTION

We are looking for a talented Senior AI Engineer to join our Engineering Frameworks Team. In this role, you will contribute to the design, development, integration, operationalization, and support of AI tools and platforms utilized by developers across the company to build solutions for their lines of business. This is a hands-on engineering role centered on GCP, Gemini and Vertex AI or comparable services, Claude Code, GitHub Copilot, MCP Servers, Java Spring Boot, and React.js. The ideal candidate will have direct, demonstrable experience building and integrating with AI tools and services, along with the ability to deliver reliable, secure, and maintainable solutions that accelerate software development and improve productivity across the organization.

Job Summary
A senior role focused on developing and supporting AI platforms, developer tools, and agentic application capabilities. This position requires significant experience delivering high-quality software solutions, applying sound application and integration patterns, and contributing to the design of secure and scalable AI capabilities. The Senior AI Engineer will own significant technical work efforts end-to-end, collaborate with development teams and technical leaders, and help establish reusable patterns for building and operating custom agents throughout the company.

Responsibilities
Develop and maintain AI platforms, tools, and frameworks used by engineers across the company, including Claude Code, GitHub Copilot, MCP servers, plugins, skills, and agentic frameworks.
Implement AI platform services, orchestration patterns, reference implementations, and shared integration components in collaboration with technical leads and architects.
Design and deliver tools that support development of custom agents and workflows, including sequential, multi-agent, and deterministic graph-based solutions.
Integrate and operationalize AI tools and services with cloud, security, development, and enterprise technology platforms.
Build secure, scalable, reliable, observable, performant, and maintainable services for custom agents and AI tool integrations.
Provide technical support and guidance to development teams building, deploying, and operating custom agents and MCP servers.
Contribute to framework lifecycle practices, including versioning, release management, documentation, adoption, support, and continuous improvement.
Implement logging, metrics, token-utilization monitoring, tracing, and other operational capabilities for AI services running on GCP.
Apply enterprise security, privacy, responsible AI, access-control, governance, cost-management, and model-risk practices to AI solutions.
Collaborate with development teams, security, and architecture to define requirements and deliver platform capabilities.
Participate in code reviews, technical discussions, troubleshooting, and knowledge-sharing activities.
Mentor junior engineers on the team as well as engineers on our development teams contributing to a culture of continuous improvement.

Education
Bachelor's degree or equivalent work experience in computer science, engineering, artificial intelligence, or a related field

Basic Qualifications
5-7 years of experience in software engineering, platform engineering, AI engineering, or a related technical discipline
Proven experience delivering high-quality software solutions in production environments
Hands-on experience building or integrating AI, LLM, developer-platform, or automation capabilities
Experience with cloud-based AI services platform such as GCP, Gemini, and Vertex AI or comparable model platforms
Solid understanding of application architecture, integration patterns, APIs, and software design principles
Experience developing Java REST APIs and services with Spring Boot and working knowledge of React.js or comparable front-end technologies
Experience with secure API integrations and OAuth 2.0 / OpenID Connect authorization patterns, including service accounts, client credentials, or delegated user access
Understanding of the software development lifecycle, CI/CD, observability, reliability, security, privacy, and responsible AI practices
Strong problem-solving skills, attention to detail, technical communication, and ability to collaborate effectively across teams

Preferred Qualifications
Hands-on experience using Claude Code and GitHub Copilot in an engineering workflow, including custom instructions, prompts, skills, plugins, or extensions
Designing or implementing custom AI agents, reusable orchestration patterns, shared integrations, or reference implementations
Building sequential, multi-agent, or deterministic graph-based agent workflows
Building or integrating MCP servers and clients to expose tools, resources, or data sources to AI agents
Enabling agent-to-agent communication using A2A or comparable protocols
Experience with Google ADK, Spring AI, LangChain, LangChain4j, or similar LLM integration libraries and SDKs
Experience with Gemini Agent Platform / Vertex AI capabilities such as model garden, model runtime, model gateway, or agent gateway
Implementing model governance controls such as GCP Model Armor, cost controls, token limits, rate limits, and access policies
Implementing logging, metrics, distributed tracing, token-utilization monitoring, and operational dashboards for AI services on GCP
Exposure to containerization, microservices, and cloud-native application architecture
Experience working with CI/CD pipelines in Harness and Azure DevOps, including automated build, test, security, and release workflows
Familiarity with Agile/Scrum methodologies and development practices for shared platform capabilities

Technical Skills Required
AI Platforms: GCP, Gemini, Vertex AI, model garden, model runtime, model gateway, and agent gateway
AI Engineering: custom agent design, sequential workflows, multi-agent systems, deterministic graph-based agents, and reusable orchestration patterns
Developer Tools: Claude Code, GitHub Copilot, custom instructions, prompts, skills, plugins, and extensions
Agent Integration: MCP servers and clients, tools, resources, data-source integrations, A2A patterns, and agent-to-agent communication
Frameworks: Google ADK, Spring AI, LangChain, LangChain4j, or comparable AI/LLM integration libraries
Application Development: Java, Spring Boot, REST APIs, React.js, microservices, and cloud-native application patterns
Security and Governance: OAuth 2.0, OpenID Connect, service accounts, delegated access, model governance, GCP Model Armor, privacy, responsible AI, and access control
Operations: CI/CD, Harness, Azure DevOps, logging, metrics, tracing, token utilization, performance, reliability, and incident support

Strengths and Capabilities
Technical Expertise: Strong, hands-on knowledge of AI/LLM integration, agent development, platform engineering, and enterprise software delivery.
Platform Proficiency: Ability to build, integrate, operate, and support AI platforms and developer toolkits using GCP, Gemini, Vertex AI, Claude Code, GitHub Copilot, MCP, and related technologies.
Application and Integration Design: Ability to apply sound design patterns and contribute to reusable orchestration patterns, shared integration components, and maintainable frameworks for custom agents and MCP services.
Technical Delivery: Ability to own substantial work efforts end-to-end, make sound technical decisions, deliver high-quality solutions, and resolve complex implementation and integration issues.
Security and Responsible AI: Ability to apply secure-by-design, privacy, governance, access-control, cost-management, and responsible AI principles to enterprise AI solutions.
Product Awareness: Ability to understand developer and business needs, provide useful feedback on platform capabilities, and contribute to continuous improvement.
Collaboration and Communication: Ability to work effectively with development teams, technical leads, product management, security, architecture, lines of business, and other stakeholders.
Mentorship and Advocacy: Ability to share knowledge, support junior engineers, and encourage effective adoption of AI tools, platforms, frameworks, and best practices.
Adaptability: Ability to learn and apply rapidly evolving AI technologies, developer tools, platform capabilities, and industry practices.

Thanks!
Aditya Kumar Singh
IT Recruiter
St. Augustine, FL 32092
Email: View email address on us.fitly.work

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